Artificial lift systems are widely used in the oil industry to enhance production from reservoirs that have levels which are too low to directly lift fluids to the surface. There are a variety of artificial lift techniques in the industry, such as Gas Lift, Hydraulic Pumping Units, Electric Submersible Pump, Progressive Cavity Pump and Rod Pump techniques. Among these, the Sucker Rod Pump technique is the most commonly used.
The reasons for rod pump failures can be broadly classified into two main categories: mechanical and chemical. Mechanical failures are caused by improper design improper manufacturing or from wear and tear during operations. Well conditions may contribute to excessive wear and tear, such as sand intrusions, gas pounding, rod cutting and asphalting. Chemical failures are caused by the corrosive nature of the fluid being pumped through the systems. For example, the fluid may contain H2S or bacteria. For rod pumps, one of the major mechanical failures is referred to as Tubing Failure, where tubing of the pump leaks due to accumulated mechanical friction and cutting events. A tubing leak does not cause a rod pump to shut down, but rather reduces the pump efficiency. Such tubing leaks are difficult to identify, because they occur downhole, and are difficult to locate via visual or sound inspection.
In a typical oil field, there are hundreds of wells, and there are many fields operated by the same organization that may have various geological formations. Well failures in oil field assets lead to production loss and can greatly increase the operational expense. Accordingly, to the extent possible, it is desirable to avoid well failures, for example by identifying anomalies in well operation prior to well failure.
It is possible, in some cases, to identify anomalies by combining different types of information such as recent performance of the well, an events log associated with the well, and performance of neighboring wells. Such anomalies, once identified, have high probability to be followed by a failure in the future. For example, such anomalies might have already been causing economic losses. Accordingly, it would be desirable to schedule either proactive maintenance or repair to reduce such losses. However, with limited number of trained personnel and resources for managing large fields, such proactive operation is difficult to accomplish.
Recently, oil fields have been increasingly instrumented, with volumes of data being collected. This data includes historical event log and time series parametric data. Such field data, along with an expert's prior knowledge regarding the types of errors encountered and in particular in the region where the oil field is located, are very useful to data mining methodologies to predict well failures. However, even these systems have disadvantages. For example, because wells often perform differently in different conditions, it may be the case that a well in a particular location may perform substantially differently than a similar well placed in a different location, for example due to the environmental conditions at the well site, or due to subsurface conditions. Accordingly, monitoring systems may still be able to compare closely-located wells to detect anomalies, any performance degradation measures (e.g., performance thresholds set at which degradation is assumed) at those wells may not be well suited to other wells at other locations. For these reasons, existing systems that monitor instrumented wells are typically limited to localized areas to avoid having to account for variances across operating conditions. Such limited-use systems are sub-optimal, at least because they cannot be applied universally across oil fields, and require each system to be monitored and/or updated individually.